Structured (JSON) logging for ML experiments with schema validation and pluggable sinks.
pip install -e ".[dev]"from mlog import get_logger, run_context
log = get_logger(project="demo", experiment="baseline", sink="stdout", validation="strict")
with run_context(run_id="run_001", tags={"team": "ml"}):
log.param("lr", 0.01)
log.metric("train.loss", 0.123, step=1)
log.event("done")